Department of Methodology and Statistics, Utrecht University.
Psychometric Research Center, Cito, Dutch Institute for Educational Measurement.
Psychol Methods. 2017 Dec;22(4):705-724. doi: 10.1037/met0000124. Epub 2017 Apr 3.
Linking and equating procedures are used to make the results of different test forms comparable. In the cases where no assumption of random equivalent groups can be made some form of linking design is used. In practice the amount of data available to link the two tests is often very limited due to logistic and security reasons, which affects the precision of linking procedures. This study proposes to enhance the quality of linking procedures based on sparse data by using Bayesian methods which combine the information in the linking data with background information captured in informative prior distributions. We propose two methods for the elicitation of prior knowledge about the difference in difficulty of two tests from subject-matter experts and explain how these results can be used in the specification of priors. To illustrate the proposed methods and evaluate the quality of linking with and without informative priors, an empirical example of linking primary school mathematics tests is presented. The results suggest that informative priors can increase the precision of linking without decreasing the accuracy. (PsycINFO Database Record
链接和等效程序用于使不同测试形式的结果具有可比性。在不能假设随机等效组的情况下，会使用某种形式的链接设计。在实践中，由于后勤和安全原因，可用于链接两个测试的信息量通常非常有限，这会影响链接程序的精度。本研究提出通过使用贝叶斯方法来增强基于稀疏数据的链接程序的质量，该方法将链接数据中的信息与信息先验分布中捕获的背景信息相结合。我们提出了两种从主题专家那里获取关于两个测试难度差异的先验知识的方法，并解释了如何在指定先验分布时使用这些结果。为了说明所提出的方法和评估具有和不具有信息先验的链接质量，提供了一个链接小学数学测试的实证示例。结果表明，信息先验可以在不降低准确性的情况下提高链接的精度。
